Non-depressed Participants Research Articles

Sadness and the continuum from well-being to depressive disorder: Findings from a representative US population sample

Sadness is a common symptom in the general population. We tested the hypothesis that sadness is an intermediate state on a continuum from well-being to major depressive disorder (MDD). Using data from The National Epidemiologic Study of Alcohol and Related Conditions III (NESARC-III), a large and representative US population sample, we assessed the prevalence of sadness, its sociodemographic and clinical correlates, using three non-overlapping groups: (i) non-depressed sad participants, (ii) non-sad non-depressed participants and (iii) depressed participants. We estimated sensitivity and specificity of sadness. Sadness was frequent in the general population 34.3%), and present in almost all participants with MDD (99.6%). Sad (N=4593) and MDD participants (N=4593) and 7889 respectively) shared common sociodemographic characteristics. Compared to controls, sad and MDD participants presented more psychiatric disorders, including anxiety, substance use, psychotic, eating and personality disorders. Sadness was an intermediate state, sad individuals reporting more psychiatric disorders than controls, but less than participants with MDD. Sadness demonstrated a very high sensitivity (99.6%), with a good specificity (83.8%) for MDD. The NESARC assessed sadness over lifetime, which may involve memorization bias. Our study confirms the existence of a depressive continuum. Sadness is frequent in general population, and shares correlates with MDD. We have also shown a continuum where sadness is an intermediate state between well-being and psychiatric disorders. With high sensitivity and specificity, sadness appears as a clear MDD prodrome and at-risk state, and may be a symptom of a transdiagnostic distress process.

Automatic Depression Prediction Using Internet Traffic Characteristics on Smartphones.

Depression is a serious mental health problem. Recently, researchers have proposed novel approaches that use sensing data collected passively on smartphones for automatic depression screening. While these studies have explored several types of sensing data (e.g., location, activity, conversation), none of them has leveraged Internet traffic of smartphones, which can be collected with little energy consumption and the data is insensitive to phone hardware. In this paper, we explore using coarse-grained meta-data of Internet traffic on smartphones for depression screening. We develop techniques to identify Internet usage sessions (i.e., time periods when a user is online) and extract a novel set of features based on usage sessions from the Internet traffic meta-data. Our results demonstrate that Internet usage features can reflect the different behavioral characteristics between depressed and non-depressed participants, confirming findings in psychological sciences, which have relied on surveys or questionnaires instead of real Internet traffic as in our study. Furthermore, we develop machine learning based prediction models that use these features to predict depression. Our evaluation shows that Internet usage features can be used for effective depression prediction, leading to F 1 score as high as 0.80.

Prevalence of complicated grief and related factors in elderly individuals in Sabzevar City, Iran.

Although often undiagnosed and untreated, prolonged grief and its conversion to complicated grief (CG) can lead to functional impairment. Given the impact of CG on mortality and quality of life in elderly individuals, this study aimed to determine the prevalence of CG and its related factors among the elderly in the city of Sabzevar in Iran. The subjects of this cross-sectional study were elderly individuals aged 60 years and older who lived Sabzevar in 2019. Participants were randomly selected in two stages. First, the grief experience of 823 elderly individuals was investigated. Second, the 247 individuals who met the inclusion criteria and had experienced grief were assessed for CG. Data were collected with a demographic information questionnaire, the Brief Grief Questionnaire, and the Geriatric Depression Scale. The prevalence of CG among the participants who had experienced grief was 18.6%. Significant differences in CG prevalence were observed among participants according to age, gender, marital status, occupation, and relationship to the deceased person (P < 0.05). The prevalence of CG was also significantly associated with the deceased person's age, gender, and cause of death; the participant being the deceased's primary caregiver and the participant being with the deceased at the time of death(P < 0.05). Furthermore, CG was significantly higher in people with mild or severe depression than in non-depressed participants (P = 0.01). The odds of CG and sub-threshold CG incidence were 2.94 times higher in women than in men and 3.64 times higher in participants with severe depression than in non-depressed participants. Complicated grief is relatively prevalent among the elderly, and it is associated with age, gender, marital status, depression status, and some variables related to the deat time of the deceased. Given the negative effects of CG on individuals and the community, appropriate planning is needed to reduce its incidence in elderly individuals who have experienced grief.

The proportion of non-depressed subjects in a study sample strongly affects the results of psychometric analyses of depression symptoms.

BackgroundRecent studies have uncovered a peculiar finding: that the strength and dimensionality of depression symptoms’ inter-relationships vary systematically across study samples with different average levels of depression severity. Our aim was to examine whether this phenomenon is driven by the proportion of non-affected subjects in the sample.MethodsCross-sectional data from the “Cohort Study on Substance Use Risk Factors” was analyzed. Self-reported depression symptoms were assessed via the Major Depressive Inventory. Symptom data were analyzed via polychoric correlations, principal component analysis, confirmatory factor analysis, Mokken scale analysis, and network analysis. Analyses were carried out across 22 subsamples containing increasingly higher proportions of non-depressed participants. Results were examined as a function of the proportion of non-depressed participants.ResultsA strong influence of the proportion of non-depressed participants was uncovered: the higher the proportion, the stronger the symptom correlations, higher their tendency towards unidimensionality, better their scalability, and higher the network edge strengths. Comparing the depressed sample with the general population sample, the average symptom correlation increased from 0.29 to 0.51; variance explained by the first eigenvalue increased from 0.36 to 0.56; fit measures from confirmatory one-factor analysis increased from 0.81 to 0.97; the H coefficient of scalability increased from 0.26 to 0.48; and the median network edge increased from 0.00 to 0.07.ConclusionsResults of psychometric analyses vary substantially as a function of the proportion of non-depressed participants in the sample being studied. This provides a possible explanation for the lack of reproducibility of previous psychometric studies.

Associations between systemic inflammation and somatic depressive symptoms: Findings from the Moli-sani study.

The link between systemic inflammation and depression has been deeply investigated, but relatively few studies explored symptom-specific associations, mostly focusing on common inflammatory biomarkers like C-reactive protein (CRP) levels. We investigated associations of low-grade inflammation with depressive symptoms assessed through a reduced version of Patient Health Questionnaire 9 (PHQ-9) in a large population-based cohort of adult Italians (N = 13 301). We built logistic regressions between each depressive symptom and composite index of systemic inflammation based on four circulating biomarkers, namely CRP, Plt, WBC, and GLR (INFLA)-score, a composite blood-based inflammation index, and with its component biomarkers, namely CRP, platelets count (Plt), white blood cells count (WBC), and granulocyte-to-lymphocyte ratio (GLR). We observed a strong association of the altered appetite/eating symptom with standardized INFLA-score (OR [95% CI] = 1.19 [1.12-1.26]; corrected p = 3.0 × 10-7 ), CRP (1.28 [1.20-1.36]; p = 1.9 × 10-13 ), and WBC (1.13 [1.06-1.20]; p = 2.3 × 10-3 ), and of tiredness/low energy with GLR (1.11 [1.05-1.17]; p = 9.4 × 10-3 ). These associations remained stable within nondepressed participants (PHQ-9 < 10), and after adjustment for the use of antidepressants, main chronic conditions, and lifestyle factors; while they were notably attenuated within depressed participants (PHQ-9 ≥ 10) and-for altered appetite only-by adjustment for obesity. This study provides a robust replication of the association previously reported between CRP and altered appetite in a large US population cohort, and supports a link between systemic inflammation, altered appetite, and tiredness. Moreover, it extends this evidence to inflammatory markers other than CRP and suggests new targets for the treatment of atypical depression.

Testing the Analytical Rumination Hypothesis: Exploring the Longitudinal Effects of Problem Solving Analysis on Depression.

Depression is a mental health condition for which individuals commonly seek treatment. However, depressive episodes often resolve on their own, even without treatment. One evolutionary perspective, the analytical rumination hypothesis (ARH), suggests that depression occurs in response to complex problems. According to this perspective, depressive symptoms promote analytical rumination, i.e., distraction-resistant thoughts about the causes of problems [causal analysis (CA)] and how they can be solved [problem-solving analysis (PSA)]. By helping individuals solve complex problems, analytical rumination may contribute to remission from depression. The aim of this study was to investigate (1) whether clinically-depressed individuals have more complex problems and engage in more CA and PSA than non-depressed and (2) the effects of CA and PSA on decreases in problem complexity, depressive symptoms, and remission from the depression. Samples of 85 patients were treated for depression with antidepressants and psychotherapy, and 49 healthy subjects were assessed three times over a 4-month period (at Weeks 1, 5, and 16). At each assessment, they completed measures of depression, analytical rumination, and problem complexity. Depressed individuals reported having more complex problems and engaging in more CA than non-depressed participants. The two groups engaged in a similar degree of PSA. Findings from a multiple regression suggested that more PSA at Week 1 was related to a decrease in depressive symptoms at Week 5, even after controlling for baseline depression, problem number, and complexity. PSA at Week 1 did not predict the remission after hospitalization or at follow-up; however, having less complex problems at the baseline made it more likely that a patient would later remit. Engaging in more CA or PSA at Week 1 did not affect perceived problem complexity at Week 5 or at follow-up. However, these findings were not statistically significant when influential observations (or outliers) were included in the analysis. Our findings suggest that PSA may contribute to a decrease in symptoms of depression over time. However, alleviations in problem complexity and remission might only be achieved if problems are initially less complex. Future directions involve exploring how PSA might contribute to decreases in depressive symptoms and other mechanisms underlying remission from depression.

Validity of the Korean Version of the Schema Mode Inventory (SMI)

This study investigated whether the schema modes have validity in Korean adults. We examined the validity and reliability of the Schema Mode Inventory (SMI) in a Korean adult sample (N = 768; Mean age = 22.29 years; range = 19-55 years; 69.3% Males). Psychometric properties, such as factor structure, internal reliability, as well as intercorrelations among subscales were assessed. Confirmatory factor analyses yield satisfying fits for a 61-item Korean Schema Mode Inventory. Thirteen Schema Mode Inventory scales were found to have adequate reliability of the original 14 schema factors. Furthermore, the SMI scales differentiated between depressed and non-depressed participants as theoretically predicted. These findings imply that the SMI is a sound instrument to measure the schema mode model in a Korean setting for assessment prior to schema therapy.

The roles of comorbidity and trauma exposure and its timing in shaping HPA axis patterns in depression

BackgroundMuch work has documented hypothalamic pituitary adrenal (HPA) axis abnormalities in major depressive disorder (MDD), but inconsistencies leave this system’s role in the illness unclear. Comparisons across studies are complicated by variation in co-morbidity (Posttraumatic Stress Disorder-PTSD, anxiety disorders), exposure to trauma, and timing of trauma (child vs. adult). Here, we examined the impact of these factors on HPA axis profiles in depression. MethodsWe recruited 5 groups of participants: MDD (n = 14), comorbid MDD + PTSD following adulthood trauma (MDD + PTSD-Adult; n = 12), comorbid MDD + PTSD following childhood trauma (MDD + PTSD-Child; n = 18), comorbid MDD + social anxiety disorder (MDD + SAD; n = 12), and non-depressed control participants who were sex and age matched to patients (combined total n = 36). HPA axis function was assessed using three challenges: stress reactivity via the Trier Social Stress Test (TSST), feedback sensitivity via a dexamethasone suppression test (DST), and central drive via a metyrapone challenge (MET). We compared hormonal responses between patient groups and their respective non-depressed controls. ResultsMDD + PTSD-Child showed low cortisol levels at baseline, and reduced adrenocorticotropic hormone (ACTH) levels at baseline and throughout the TSST. MDD-only, MDD + PTSD-Adult, and MDD + SAD did not differ from non-depressed controls in HPA axis responses to the TSST. Controlling for childhood trauma severity, the reduced baseline levels in MDD + PTSD-Child were no longer significant and significantly reduced baseline cortisol levels emerged for MDD + PTSD-Adult. No diagnostic group effects were detected with DST and MET. Childhood maltreatment subtypes were associated with unique HPA axis responses to TSST and MET. ConclusionComorbidity and trauma exposure, as well as their timing and type, contribute to inconsistencies in the depression literature and must be included in efforts to clarify the role of the HPA axis in MDD.

Pro-inflammatory markers and fatigue in patients with depression: A case-control study

The aim of this work was to investigate differences between depressed subjects (PG) and non-depressed healthy control participants (HCG) with regard to fatigue dimensions and inflammation. For this purpose, 43 participants in the PG and 51 participants in the HCG were included in the study. IL-6, IL-1β, TNF-α, IFN-γ, and CRP were assessed in venous blood samples. Fatigue and depression were assessed using the FIS-D and BDI-FS questionnaires. Main results showed higher BDI-FS values in PG. Moreover, PG showed mean differences for fatigue dimensions when compared to the HCG. For the pro-inflammatory markers, a moderate group effect was found between PG and HCG which was mainly caused by IL-6. Correlations between TNF-α and BDI-FS, TNF-α and cognitive fatigue, TNF-α and psychosocial fatigue were found within the PG. In the HCG, correlations were found between IL-6, TNF-α and somatic fatigue, as well as IL-6 and cognitive fatigue. Significant correlations were found between the psychological variables in both groups. All results were controlled for the confounding variables gender, age, BMI and multiple comparisons. These results suggest the presence of inflammation in both depression and fatigue. However, each correlates with different pro-inflammatory parameters, suggesting a biological heterogeneity.

Prediction of depression cases, incidence, and chronicity in a large occupational cohort using machine learning techniques: an analysis of the ELSA-Brasil study.

Depression is highly prevalent and marked by a chronic and recurrent course. Despite being a major cause of disability worldwide, little is known regarding the determinants of its heterogeneous course. Machine learning techniques present an opportunity to develop tools to predict diagnosis and prognosis at an individual level. We examined baseline (2008-2010) and follow-up (2012-2014) data of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), a large occupational cohort study. We implemented an elastic net regularization analysis with a 10-fold cross-validation procedure using socioeconomic and clinical factors as predictors to distinguish at follow-up: (1) depressed from non-depressed participants, (2) participants with incident depression from those who did not develop depression, and (3) participants with chronic (persistent or recurrent) depression from those without depression. We assessed 15 105 and 13 922 participants at waves 1 and 2, respectively. The elastic net regularization model distinguished outcome levels in the test dataset with an area under the curve of 0.79 (95% CI 0.76-0.82), 0.71 (95% CI 0.66-0.77), 0.90 (95% CI 0.86-0.95) for analyses 1, 2, and 3, respectively. Diagnosis and prognosis related to depression can be predicted at an individual subject level by integrating low-cost variables, such as demographic and clinical data. Future studies should assess longer follow-up periods and combine biological predictors, such as genetics and blood biomarkers, to build more accurate tools to predict depression course.

A bayesian approach to examining default mode network functional connectivity and cognitive performance in major depressive disorder

To reconcile the inconsistency of the association between the resting-state functional connectivity (RSFC) and cognitive performance in healthy and depressed groups due to high variance of both measures, we proposed a Bayesian spatio-temporal model to precisely and accurately estimate the RSFC in depressed and nondepressed participants. This model was employed to estimate spatially-adjusted functional connectivity (saFC) in the extended default mode network (DMN) that was hypothesized to correlate with cognitive performance in both depressed and nondepressed. Multiple linear regression models were used to study the relationship between DMN saFC and cognitive performance scores measured in the following four cognitive domains while adjusting for age, sex, and education. In ROI pairs including the posterior cingulate (PCC) and anterior cingulate (ACC) cortex regions, the relationship between connectivity and cognition was found only with the Bayesian approach. Moreover, only the Bayesian approach was able to detect a significant diagnostic difference in the association in ROI pairs, including both PCC and ACC regions, due to smaller variance for the saFC estimator. The results confirm that a reliable and precise saFC estimator, based on the Bayesian model, can foster scientific discovery that may not be feasible with the conventional ROI-based FC estimator (denoted as ‘AVG-FC’).

Emotional complexity across the life story: Elevated negative emodiversity and diminished positive emodiversity in sufferers of recurrent depression

BackgroundGreater diversity in the experience of negative and positive emotions – emodiversity - is associated with better mental health outcomes in the general population (Quoidbach et al. 2014). However, conceptual accounts of depression suggest this might differ in clinical depression. In this study, the diversity of negative and positive emotion experiences as remembered by a recurrently depressed sample and a never-depressed control group were compared. MethodsEmodiversity was assessed using a life structure card sort task which allowed for the assessment of memory for emotional experience over the life course. Depressed (n=34) and non-depressed (n=34) participants completed the card sort task, from which emodiversity metrics were calculated for negative and positive emotion experience. ResultsDepressed individuals showed recollections of enhanced emodiversity across negative emotion but reduced emodiversity across positive emotion, relative to never-depressed individuals. LimitationsThis study involved a relatively small sample size. DiscussionThis study indicates that greater diversity of negative emotion experience, which has been interpreted as a protective factor against depressed mood in community samples (Quoidbach et al., 2014), instead characterises the remembered experience of recurrent clinical depression. The finding that positive emodiversity is adaptive in depression suggests that therapeutic outcomes may be improved by facilitating exposure to a diverse range of positive emotions. These findings indicate that the relationship between emotion diversity and mental health is more complex than hitherto assumed.

WITHDRAWN: The relationship between nightmares, depression and suicide

ObjectivePrevious studies investigating the association between nightmares and suicide have yielded different results. We aimed to investigate whether nightmares, directly or indirectly, influence the incidence of suicide.MethodsWe used a prospective cohort study, based on 40,902 participants with a mean follow-up duration of 19.0 years. Cox proportional hazards models with attained age as time-scale were fitted to estimate hazard ratios (HR) of suicide with 95% confidence intervals (CI) as a function of the presence or absence of depression and nightmares. Mediation analysis was used to asses to what extent the relationship between nightmares and the incidence rate of suicide could be mediated by depression.ResultsNo association was observed between nightmares and the incidence of suicide among participants without depression. Compared with non-depressed participants without nightmares, the incidence of suicide among participants with a diagnosis of depression was similar among those with and without nightmares (HR 12.3, 95% CI 5.55–27.2 versus HR 13.2, 95% CI 7.25–24.1). The mediation analysis revealed no significant effects of nightmares on suicide incidence. However, the incidence of depression during follow-up was higher among those who suffered from nightmares than among those who did not (p < 0.001).ConclusionsOur findings indicate that nightmares have no influence on the incidence rate of suicide, but may reflect pre-existing depression. This is supported by a recent discovery of a strong genetic correlation of nightmares with depressive disorders, with no evidence that nightmares would predispose to psychiatric illness or psychological problems. Interventions targeting both depression and nightmares, when these conditions co-occur, may provide additional therapeutic benefit.

Event-Related Potentials to Changes in Sound Intensity Demonstrate Alterations in Brain Function Related to Depression and Aging.

Measures of the brain’s automatic electrophysiological responses to sounds represent a potential tool for identifying age- and depression-related neural markers. However, these markers have rarely been studied related to aging and depression within one study. Here, we investigated auditory event-related potentials (ERPs) in the brain that may show different alterations related to aging and depression. We used an oddball condition employing changes in sound intensity to investigate: (i) sound intensity dependence; (ii) sensory gating; and (iii) change detection, all within a single paradigm. The ERPs of younger (18–40 years) and older (62–80 years) depressed female participants and age-matched non-depressed participants were measured. Intensity dependence was examined as the difference between N1 responses to repeated high- and low-intensity sounds, sensory gating as N1 responses to rare and repeated sounds, and change detection as indexed by the mismatch negativity (MMN). We found that intensity dependence was greater in older participants than younger ones, indicating effects related to aging but not to depression. For sensory gating, we found depression- and age-related alterations as increased N1 responses. No group differences were found for MMN. Although a sensory gating deficit was expected in older adults, this study is the first to demonstrate age-related overexcitability in sound intensity dependency. The results indicate that automatic brain responses to sound intensity changes are suitable for studying age- and depression-related neural markers but may not be sensitive enough to differentiate the effects of aging and depression.

Adverse life events and late-life cognitive decline in a Chinese cohort: The Shanghai Aging Study.

This study aimed to demonstrate the association between adverse life events (ALEs) and the risk of late-life cognitive decline in older community-dwelling individuals in China. We prospectively followed up 1657 dementia-free participants with ALE data at baseline in the Shanghai Aging Study. The cohort was categorized into four subgroups (depression with ALEs, depression without ALEs, no depression with ALEs, and no depression without ALEs). Cox regressions were conducted to estimate the hazard ratio (HR) for incident dementia stratified by all participants and depressed and nondepressed participants. We identified 168 incident dementia cases over a mean period of 5.2 years. The cumulative dementia incidence in nondepressed participants with ALEs was the lowest among the four subgroups. Nondepressed participants with ALEs had a lower risk of incident dementia (HR [95% CI]: 0.50 [0.27-0.92], P = .0267) than those without ALEs, adjusted for age, sex, education, apolipoprotein E ε4 (APOE ε4), body mass index, cigarette smoking, heart disease, hypertension, diabetes, stroke, Mini-Mental State Examination (MMSE) at baseline, and anxiety. This study explored a significant inverse association between ALEs and the risk of incident cognitive decline among older adults without depression in China. Interventions for depression prevention immediately after ALEs may reduce the risk of cognitive decline later in life.

An Acoustic Study of Fundamental Frequency and Pauses in Depressive Teenagers in Thailand: A Pilot Study

Depression is a major public health problem among Thais. It has been reported that 30% of 70 million people living in Thailand suffer from depression. Suicide is a potential end result from mental illness, which normally involves depression. Diagnosis and treatment are key factors in the prevention of depression. In traditional diagnosis, there are two key methods of testing: (i) a screening test and interview and (ii) a biomarker test. In recent years, detecting depression with speech—a kind of biomarker test— has gained high acceptance. Cues of suprasegments in speech, such as pauses, loudness, tones, rhythm, and phonation, have been scientifically proven using acoustic methods of being indicators of depression. This paper has two main objectives: (i) to conduct a review of the use of suprasegments as cues and an analysis of the cues capable of indicating depression in Thailand and (ii) to analyze an acoustic study of pitch measured by the fundamental frequency and silent pause length in depressed and non-depressed participants. The method used in the study is the acoustic method of linguistics. Praat program version 6.2.09 was used to analyze the data. This is a pilot study of three depressed Thai students aged 20 compared with three non-depressed Thai participants. We propose a new perspective upon Thai language speech indicators that combines two or more cues in detecting depression (e.g. depression inventory with pause duration and word signs). Interestingly, it was found that the pitch of Thai tones may not be an appropriate cue for depression in Thais. This result conflicts with previous research conducted in other non-tonal languages. The results of this study lay the foundation for a Thai speech index for depression that can be further developed for the detection of depression.

Bidirectional longitudinal associations of omega-3 polyunsaturated fatty acid plasma levels with depressive disorders

BackgroundTemporality of the association of low omega-3 polyunsaturated fatty acid (n-3 PUFA) plasma levels with depression remains questionable. To determine the underlying nature of these associations, this study examined the bidirectional longitudinal associations of n-3 PUFA plasma levels with (presence, onset and course of) depressive disorders and symptoms. MethodsBaseline (n = 2912, 28.6% with current depressive disorder) and 6-year follow-up data (n = 1966, 13.0% with current depressive disorder) of the Netherlands Study of Depression and Anxiety (NESDA) were used. Depression diagnoses and symptoms were based on psychiatric interviews and self-report questionnaires. N-3 PUFA levels (ratio of total fatty acids (mmol%)), were assessed using nuclear magnetic resonance. ResultsUsing two waves of data, n-3 PUFA levels were lower among depressed persons, as compared to healthy controls (Beta = −0.047, SE = 0.011, p < .001). Nevertheless, baseline n-3 PUFA levels were not consistently associated with subsequent change in depressive symptoms, onset or remission of depressive disorders over 6 years. Furthermore, the difference in n-3 PUFA levels detected at baseline between depressed and non-depressed participants tended to dissipate over 6 years (depression-by-time estimate: p = .011). Finally, subjects depressed both at baseline and at 6-year follow up had consistently lower n-3 PUFA levels over the entire follow-up as compared to those who had never been depressed. Change in depressive disorders across waves was not consistently accompanied by change in n-3 PUFA levels over time. LimitationsNo data on intermediate time points and EPA levels were available. ConclusionsDespite significant cross-sectional associations between n-3 PUFA plasma levels and depressive disorders and severity, this 6-year longitudinal study could not confirm an uni- or bidirectional association over time. The association between depression and n-3 PUFA plasma levels is unlikely to be causal.

Association between Neighborhood Environment and Quality of Sleep in Older Adult Residents Living in Japan: The JAGES 2010 Cross-Sectional Study.

Poor sleep is associated with lifestyle, however, few studies have addressed the association between sleep quality and the neighborhood environment. This study aimed to investigate the associations between living environment factors and sleep quality in older people. Participants were community-dwelling people aged ≥65 years who participated in the 2010 Japanese Gerontological Evaluation Study. The data of 16,650 people (8102 men, 8548 women) were analyzed. Sleep quality (good or poor) was evaluated using a self-administered questionnaire. Multilevel Poisson regression analysis stratified by depressive status (measured by the Geriatric Depression Scale-15 [GDS]) was conducted with sleep quality as the dependent variable and social and physical environmental factors as explanatory variables. The 12,469 non-depressive respondents and 4181 depressive respondents were evaluated. The regression analysis indicated that non-depressive participants slept better if they lived in environments with few hills or steps (prevalence ratio [PR] = 0.75, 95% CI: 0.56–0.9) and with places where they felt free to drop in (PR = 0.51, 95% CI: 0.26–0.98). For depressive participants, these associations were not evident. Living alone, poor self-rated health, low income, and unemployment were associated with poor sleep quality. In addition to support with these individual factors, improving environmental factors at the neighborhood level may improve the sleep quality of community-dwelling older adults.

Health-related Quality of Life of Nurses Working in Tertiary Care Hospital of Karachi.

Objective:The aim of this study was to assess nurses’ health-related quality of life.Methods:This cross-sectional analytical study was accomplished among 154 nurses. Data were collected from two tertiary care hospitals of Karachi. Consent was taken prior to data collection from every participant. Questionnaire Short Form Health Survey-26 (SF-26) and Patients Health Questionnaire-9(PHQ-9) were used as a study tool. Data were analyzed through SPSS version 21.Results:ANOVA and T-test confirmed that energy/fatigue domain differed significantly with level of education, duty shift and monthly income with p-values 0.025, 0.001 and 0.006 respectively. It was observed that mean scores of physical functioning, role limitation due to physical health and pain domains differ significantly between depressive and non-depressive participants, with p-values 0.045, 0.01 and 0.005 respectively.Conclusions:Health related quality of life differs in comparison of physical health domain with depressive and non-depressive nurses. Only energy/fatigue domain was significantly associated with level of education, duty shift and monthly income of nurses.

Association between depressive symptoms and poor sleep quality among Han and Manchu ethnicities in a large, rural, Chinese population.

ObjectivesTo estimate the relationship between sleep quality and depression, among Han and Manchu ethnicities, in a rural Chinese population.MethodsA sample of 8,888 adults was selected using a multistage cluster and random sampling method. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). Depressive symptoms were assessed via the Center for Epidemiological Survey, Depression Scale (CES-D). Logistic regression was conducted to assess associations between sleep quality and depression.ResultsThe prevalence of poor sleep quality and depression in the Manchus (20.74% and 22.65%) was significantly lower than that in the Hans (29.57% and 26.25%), respectively. Depressive participants had higher odds ratios of global and all sub PSQI elements than non-depressive participants, both among the Hans and the Manchus. Additive interactions were identified between depressive symptoms and ethnicity with global and four sub-PSQI elements, including subjective sleep quality, sleep disturbance, use of sleep medication and daytime dysfunction.ConclusionsThe findings revealed that the prevalence of poor sleep quality and depression among the Hans was greater than among the Manchus. Depression was associated with higher odds of poor sleep quality.